package com.hlz.flink.wc;

import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

/**
 * 流处理
 *
 * @author Hongliang Zhu
 * @create 2022-11-27 14:44
 */
public class BoundedStreamWordCount {

    public static void main(String[] args) throws Exception {
        // 创建流式的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 读取文件
        DataStreamSource<String> lineStreamSource = env.readTextFile("input/words.txt");

        // 转换计算
        SingleOutputStreamOperator<Tuple2<String, Long>> outputStreamOperator = lineStreamSource.flatMap((String line, Collector<Tuple2<String, Long>> out) -> {
            String[] words = line.split(" ");
            for (String word : words) {
                out.collect(Tuple2.of(word, 1L));
            }
        }).returns(Types.TUPLE(Types.STRING, Types.LONG));

        // 分组
        KeyedStream<Tuple2<String, Long>, String> keyedStream = outputStreamOperator.keyBy(value -> value.f0);
        // 求和
        SingleOutputStreamOperator<Tuple2<String, Long>> sum = keyedStream.sum(1);

        sum.print();

        // 启动执行
        env.execute();
    }
}
